I consider some hitherto unexplored examples of teleological language in the sciences. In explicating these examples, I aim to show (a) that such language is not the sole preserve of the biological sciences, and (b) that not all such talk is reducible to the ascription of functions. In chemistry and biochemistry, scientists explaining molecular rearrangements and protein folding talk informally of molecules rearranging “in order to” maximize stability. Evolutionary biologists, meanwhile, often speak of traits evolving “in order to” optimize some (...) fitness-relevant variable. I argue that in all three contexts such locutions are best interpreted as shorthands for more detailed explanations which, were we to spell them out in full, would show that the relevant process would robustly converge towards the same end-point despite variation in initial conditions. This suggests that, in biology, such talk presupposes a substantial form of adaptationism. The upshot is that such shorthands may be more applicable in the physical sciences than the biological. (shrink)

The intimacy problems for functionalism stem from the worry that if functional properties are defined in terms of their causes and effects then such functional properties seem to be too intimately connected to these purported causes and effects. I distinguish three different ways the intimacy problems can be filled out – in terms of necessary connections, analytic connections and vacuous explanations. I argue that none of these present serious problems. Instead, they bring out some important and over-looked features of functionalism.

Despite the voluminous literature on biological functions produced over the last 40 years, few philosophers have studied the concept of function as it is used in neuroscience. Recently, Craver (forthcoming; also see Craver 2001) defended the causal role theory against the selected effects theory as the most appropriate theory of function for neuroscience. The following argues that though neuroscientists do study causal role functions, the scope of that theory is not as universal as claimed. Despite the strong prima facie superiority (...) of the causal role theory, the selected effects theory (when properly developed) can handle many cases from neuroscience with equal facility. It argues this by presenting a new theory of function that generalizes the notion of a ‘selection process’ to include processes such as neural selection, antibody selection, and some forms of learning—that is, to include structures that have been differentially retained as well as those that have been differentially reproduced. This view, called the generalized selected effects theory of function, will be defended from criticism and distinguished from similar views in the literature. (shrink)

What is the biological function of perception? I hold perception, especially visual perception in humans, has the biological function of accurately representing the environment. Tyler Burge argues this cannot be so in Origins of Objectivity (Oxford, 2010), for accuracy is a semantical relationship and not, as such, a practical matter. Burge also provides a supporting example. I rebut the argument and the example. Accuracy is sometimes also a practical matter if accuracy partly explains how perception contributes to survival and reproduction.

We discuss explanation of an earlier event by a later event, and argue that prima facie cases of backwards event explanation are ubiquitous. Some examples: (1) I am tidying my flat because my brother is coming to visit tomorrow. (2) The scarlet pimpernels are closing because it is about to rain. (3) The volcano is smoking because it is going to erupt soon. We then look at various ways people might attempt to explain away these prima facie cases by arguing (...) that in each case the 'real' explanation is something else. We argue that none of the explaining-away strategies are successful, and so any plausible account of explanation should either make room for backwards explanation, or have a good story to tell about why it doesn't have to. (shrink)

Both von Neumann and Wiener were outsiders to biology. Both were inspired by biology and both proposed models and generalizations that proved inspirational for biologists. Around the same time in the 1940s von Neumann developed the notion of self reproducing automata and Wiener suggested an explication of teleology using the notion of negative feedback. These efforts were similar in spirit. Both von Neumann and Wiener used mathematical ideas to attack foundational issues in biology, and the concepts they articulated had lasting (...) effect. But there were significant differences as well. Von Neumann presented a how-possibly model, which sparked interest by mathematicians and computer scientists, while Wiener collaborated more directly with biologists, and his proposal influenced the philosophy of biology. The two cases illustrate different strategies by which mathematicians, the “professional outsiders” of science, can choose to guide their engagement with biological questions and with the biological community, and illustrate different kinds of generalizations that mathematization can contribute to biology. The different strategies employed by von Neumann and Wiener and the types of models they constructed may have affected the fate of von Neumann’s and Wiener’s ideas – as well as the reputation, in biology, of von Neumann and Wiener themselves. (shrink)

In ‘A modal theory of function’, I gave an argument against all existing theories of function and outlined a new theory. Karen Neander and Alex Rosenberg argue against both my negative and my positive claim. My aim here is not merely to defend my account from their objections, but to (a) very briefly point out that the new account of etiological function they propose in response to my criticism cannot avoid the circularity worry either and, more importantly, to (b) highlight, (...) and attempt to make precise, an important feature of my modal theory that may have been understated in the original paper – that function attributions depend on the explanatory project at hand. (shrink)

I clarify some of the details of the modal theory of function I outlined in Nanay (2010): (a) I explicate what it means that the function of a token biological trait is fixed by modal facts; (b) I address an objection to my trait type individuation argument against etiological function and (c) I examine the consequences of replacing the etiological theory of function with a modal theory for the prospects of using the concept of biological function to explain mental content.

The function of a trait token is usually defined in terms of some properties of other (past, present, future) tokens of the same trait type. I argue that this strategy is problematic, as trait types are (at least partly) individuated by their functional properties, which would lead to circularity. In order to avoid this problem, I suggest a way to define the function of a trait token in terms of the properties of the very same trait token. To able to (...) allow for the possibility of malfunctioning, some of these properties need to be modal ones: a function of a trait is to do F just in case its doing F would contribute to the inclusive fitness of the organism whose trait it is. Function attributions have modal force. Finally, I explore whether and how this theory of biological function could be modified to cover artifact function. (shrink)

Review of Peter Mc. Laughlin *What Functions Explain" (2001).

Does mathematics ever play an explanatory role in science? If so then this opens the way for scientific realists to argue for the existence of mathematical entities using inference to the best explanation. Elsewhere I have argued, using a case study involving the prime-numbered life cycles of periodical cicadas, that there are examples of indispensable mathematical explanations of purely physical phenomena. In this paper I respond to objections to this claim that have been made by various philosophers, and I discuss (...) potential future directions of research for each side in the debate over the existence of abstract mathematical objects. Introduction: Mathematical Explanation Indispensability and Explanation Is the Mathematics Indispensable to the Explanation? 3.1 Object-level arbitrariness 3.2 Concept-level arbitrariness 3.3 Theory-level arbitrariness Is the Explanandum ‘Purely Physical’? Is the Mathematics Explanatory in Its Own Right? Does Inference to the Best Explanation Apply to Mathematics? 6.1 Leng's first argument 6.2 Leng's second argument 6.3 Leng's third argument Conclusions CiteULike Connotea Del.icio.us What's this? (shrink)

Robert Batterman examines a form of scientific reasoning called asymptotic reasoning, arguing that it has important consequences for our understanding of the scientific process as a whole. He maintains that asymptotic reasoning is essential for explaining what physicists call universal behavior. With clarity and rigor, he simplifies complex questions about universal behavior, demonstrating a profound understanding of the underlying structures that ground them. This book introduces a valuable new method that is certain to fill explanatory gaps across disciplines.

This essay analyzes and develops recent views about explanation in biology. Philosophers of biology have parted with the received deductive-nomological model of scientific explanation primarily by attempting to capture actual biological theorizing and practice. This includes an endorsement of different kinds of explanation (e.g., mathematical and causal-mechanistic), a joint study of discovery and explanation, and an abandonment of models of theory reduction in favor of accounts of explanatory reduction. Of particular current interest are philosophical accounts of complex explanations that appeal (...) to different levels of organismal organization and use contributions from different biological disciplines. The essay lays out one model that views explanatory integration across different disciplines as being structured by scientific problems. I emphasize the philosophical need to take the explanatory aims pursued by different groups of scientists into account, as explanatory aims determine whether different explanations are competing or complementary and govern the dynamics of scientific practice, including interdisciplinary research. I distinguish different kinds of pluralism that philosophers have endorsed in the context of explanation in biology, and draw several implications for science education, especially the need to teach science as an interdisciplinary and dynamic practice guided by scientific problems and explanatory aims. (shrink)

Batterman ([2010]) raises a number of concerns for the inferential conception of the applicability of mathematics advocated by Bueno and Colyvan ([2011]). Here, we distinguish the various concerns, and indicate how they can be assuaged by paying attention to the nature of the mappings involved and emphasizing the significance of interpretation in this context. We also indicate how this conception can accommodate the examples that Batterman draws upon in his critique. Our conclusion is that ‘asymptotic reasoning’ can be straightforwardly accommodated (...) within the inferential conception. (shrink)

This paper concerns the question whether there exists an objective distinction between explanatory and non-explanatory demonstrations. It distinguishes between a static and a dynamic approach to explanatory demonstration, it discusses the relevance of this distinction to mathematical practice, and considers the relation of mathematical explanation to mathematical understanding.

We defend Joseph Melia's thesis that the role of mathematics in scientific theory is to 'index' quantities, and that even if mathematics is indispensable to scientific explanations of concrete phenomena, it does not explain any of those phenomena. This thesis is defended against objections by Mark Colyvan and Alan Baker.

Reasoning under uncertainty, that is, making judgements with only partial knowledge, is a major theme in artificial intelligence. Professor Paris provides here an introduction to the mathematical foundations of the subject. It is suited for readers with some knowledge of undergraduate mathematics but is otherwise self-contained, collecting together the key results on the subject, and formalising within a unified framework the main contemporary approaches and assumptions. The author has concentrated on giving clear mathematical formulations, analyses, justifications and consequences of the (...) main theories about uncertain reasoning, so the book can serve as a textbook for beginners or as a starting point for further basic research into the subject. It will be welcomed by graduate students and research workers in logic, philosophy, and computer science as a textbook for beginners, a starting point for further basic research into the subject, and not least, an account of how mathematics and artificial intelligence can complement and enrich each other. (shrink)

After reviewing some different indispensability arguments, I distinguish several different ways in which mathematics can make an important contribution to a scientific explanation. Once these contributions are highlighted it will be possible to see that indispensability arguments have little chance of convincing us of the existence of abstract objects, even though they may give us good reason to accept the truth of some mathematical claims. However, in the concluding part of this paper, I argue that even though there is a (...) valid indispensability argument for realism about some mathematical claims, this argument is problematic as it begs the question at issue. This challenge to indispensability arguments is then used to suggest that if mathematics is making these sorts of contributions to science, then it may be the case that mathematical claims receive some non-empirical support prior to their application in scientific explanation. (shrink)

The Enhanced Indispensability Argument (Baker [ 2009 ]) exemplifies the new wave of the indispensability argument for mathematical Platonism. The new wave capitalizes on mathematics' role in scientific explanations. I will criticize some analyses of mathematics' explanatory function. In turn, I will emphasize the representational role of mathematics, and argue that the debate would significantly benefit from acknowledging this alternative viewpoint to mathematics' contribution to scientific explanations and knowledge.

Recent accounts of the role of diagrams in mathematical reasoning take a Platonic line, according to which the proof depends on the similarity between the perceived shape of the diagram and the shape of the abstract object. This approach is unable to explain proofs which share the same diagram in spite of drawing conclusions about different figures. Saccheri’s use of the bi-rectangular isosceles quadrilateral in Euclides Vindicatus provides three such proofs. By forsaking abstract objects it is possible to give a (...) natural explanation of Saccheri’s proofs as well as standard geometric proofs and even number-theoretic proofs. (shrink)

How regular do mechanisms need to be, in order to count as mechanisms? This paper addresses two arguments for dropping the requirement of regularity from the definition of a mechanism, one motivated by examples from the sciences and the other motivated by metaphysical considerations regarding causation. I defend a broadened regularity requirement on mechanisms that takes the form of a taxonomy of kinds of regularity that mechanisms may exhibit. This taxonomy allows precise explication of the degree and location of regular (...) operation within a mechanism, and highlights the role that various kinds of regularity play in scientific explanation. I defend this regularity requirement in terms of regularity’s role in individuating mechanisms against a background of other causal processes, and by prioritizing mechanisms’ ability to serve as a model of scientific explanation, rather than as a metaphysical account of causation. It is because mechanisms are regular, in the expanded sense described here, that they are capable of supporting the kinds of generalizations that figure prominently in scientific explanations. (shrink)

Leuridan (2010) argued that mechanisms cannot provide a genuine alternative to laws of nature as a model of explanation in the sciences, and advocates Mitchell’s (1997) pragmatic account of laws. I first demonstrate that Leuridan gets the order of priority wrong between mechanisms, regularity, and laws, and then make some clarifying remarks about how laws and mechanisms relate to regularities. Mechanisms are not an explanatory alternative to regularities; they are an alternative to laws. The existence of stable regularities in nature (...) is necessary for either model of explanation: regularities are what laws describe and what mechanisms explain. (shrink)

The sixteenth and seventeenth centuries marks a period of transition between the vitalistic ontology that had dominated Renaissance natural philosophy and the Early Modern mechanistic paradigm endorsed by, among others, the Cartesians and Newtonians. This paper will focus on how the tensions between vitalism and mechanism played themselves out in the context of sixteenth and seventeenth century chemistry and chemical philosophy, particularly in the works of Paracelsus, Jan Baptista Van Helmont, Robert Fludd, and Robert Boyle. Rather than argue that these (...) natural philosophers each embraced either fully vitalistic or fully mechanistic ontologies, I hope to demonstrate that these thinkers adhered to complicated and nuanced ontologies that cannot be described in either purely vitalistic or purely mechanistic terms. A central feature of my argument is the claim that a corpuscularian theory of matter does not entail a strictly mechanistic and reductionistic account of chemical properties. I also argue that what marks the shift from pre-modern vitalistic chemical philosophy to the modern chemical philosophy that marked the Chemical Revolution is not the victory of mechanism and reductionism in chemistry but, rather, the shift to a physicalistic and naturalistic account of chemical properties and vital spirits. (shrink)

Evolutionary developmental biology (evo-devo) is considered a ‘mechanistic science,’ in that it causally explains morphological evolution in terms of changes in developmental mechanisms. Evo-devo is also an interdisciplinary and integrative approach, as its explanations use contributions from many fields and pertain to different levels of organismal organization. Philosophical accounts of mechanistic explanation are currently highly prominent, and have been particularly able to capture the integrative nature of multifield and multilevel explanations. However, I argue that evo-devo demonstrates the need for a (...) broadened philosophical conception of mechanisms and mechanistic explanation. Mechanistic explanation (in terms of the qualitative interactions of the structural parts of a whole) has been developed as an alternative to the traditional idea of explanation as derivation from laws or quantitative principles. Against the picture promoted by Carl Craver, that mathematical models describe but do not explain, my discussion of cases from the strand of evo-devo which is concerned with developmental processes points to qualitative phenomena where quantitative mathematical models are an indispensable part of the explanation. While philosophical accounts have focused on the actual organization and operation of mechanisms, properties of developmental mechanisms that are about how a mechanism reacts to modifications are of major evolutionary significance, including robustness, phenotypic plasticity, and modularity. A philosophical conception of mechanisms is needed that takes into account quantitative changes, transient entities and the generation of novel types of entities, feedback loops and complex interaction networks, emergent properties, and, in particular, functional-dynamical aspects of mechanisms, including functional (as opposed to structural) organization and distributed, system-wide phenomena. I conclude with general remarks on philosophical accounts of explanation. (shrink)

This paper will examine the nature of mechanisms and the distinction between the relevant and irrelevant parts involved in a mechanism’s operation. I first consider Craver’s account of this distinction in his book on the nature of mechanisms, and explain some problems. I then offer a novel account of the distinction that appeals to some resources from Mackie’s theory of causation. I end by explaining how this account enables us to better understand what mechanisms are and their various features.

Not all models are explanatory. Some models are data summaries. Some models sketch explanations but leave crucial details unspecified or hidden behind filler terms. Some models are used to conjecture a how-possibly explanation without regard to whether it is a how-actually explanation. I use the Hodgkin and Huxley model of the action potential to illustrate these ways that models can be useful without explaining. I then use the subsequent development of the explanation of the action potential to show what is (...) required of an adequate mechanistic model. Mechanistic models are explanatory. (shrink)

There is more than one explanation for the evolution of sexual reproduction. This paper investigates the possibility that this pluralism exists because these different explanations rely on intuitions provided by different philosophical theories of explanation, namely unifying views and causal mechanical views. I conclude that this is not the case.

The interventionist account of causal explanation, in the version presented by Jim Woodward (2003), has been recently claimed capable of buttressing the widely felt—though poorly understood—hunch that high-level, relatively abstract explanations, of the sort provided by sciences like biology, psychology and economics, are in some cases explanatorily optimal. It is the aim of this paper to show that this is mistaken. Due to a lack of effective constraints on the causal variables at the heart of the interventionist causal-explanatory scheme, as (...) presently formulated it is either unable to prefer high-level explanations to low, or systematically overshoots, recommending explanations at so high of a level as to be virtually vacuous. (shrink)

This paper argues that the increasingly dominant new mechanistic approach to scientific explanation, as developed to date, does not shed new light on explanatory practice. First, I systematize the explanatory account, one according to which explanations are mechanistic models that satisfy three desiderata: 1) they must represent causal relations, 2) describe the proper parts, and 3) depict the system at the right ‘level.’ Then I argue that even the most promising attempts to flesh out these constraints have fallen far short. (...) Finally, I offer a diagnosis of the mechanistic project, locating a common source of both its virtues and shortcomings. (shrink)

One of the main early forms of “functionalism,” developed by writers like Jerry Fodor and William Lycan, focused on “mechanistic” explanation in the special sciences and argued that “functional properties” in psychology were continuous in nature with the special science properties posited in such mechanistic explanations. I dub the latter position“Continuity Functionalism” and use it to critically examine the “Standard Picture” of the metaphysics of functionalism which takes “functional” properties to be second-order properties and claims there are two metaphysical forms (...) of “functionalism,” in so-called “role” and “realizer” functionalism. Looking at mechanistic explanations, I show that the “functional properties” posited in the special sciences are not second-order properties and that Continuity Functionalism is a distinctive metaphysical version of functionalism not covered by the Standard Picture. My conclusion is that the Standard Picture offers us a false dichotomy of ways to be a “functionalist” and that “functionalists” thus need to look once more to the special sciences to configure their views, thus eschewing the machinery inherited from “analytic” philosophers. (shrink)

During the past decade, social mechanisms and mechanism-based ex- planations have received considerable attention in the social sciences as well as in the philosophy of science. This article critically reviews the most important philosophical and social science contributions to the mechanism approach. The first part discusses the idea of mechanism- based explanation from the point of view of philosophy of science and relates it to causation and to the covering-law account of explanation. The second part focuses on how the idea (...) of mechanisms has been used in the social sciences. The final part discusses recent developments in analytical sociology, covering the nature of sociological explananda, the role of theory of action in mechanism-based explanations, Merton’s idea of middle-range theory, and the role of agent-based simulations in the development of mechanism-based explanations. (shrink)

Historically embryogenesis has been among the most philosophically intriguing phenomena. In this paper I focus on one aspect of biological development that was particularly perplexing to the ancients: self-organisation. For many ancients, the fact that an organism determines the important features of its own development required a special model for understanding how this was possible. This was especially true for Aristotle, Alexander, and Simplicius who all looked to contemporary technology to supply that model. However, they did not all agree on (...) what kind of device should be used. In this paper I explore the way these ancients made use of technology as a model for the developing embryo. However, my purpose here is more than just the historical interest of knowing which devices were used by whom and how each of them worked; I shall largely ignore the details of how the various devices actually worked. Instead I shall look at the use of technology from a philosophical perspective. As we shall see, the different choices of device reveal fundamental differences in the way each thinker understood the nature of biological development itself. Thus, the central aim of this paper is to examine, not who used what devices and how they worked, but why they used those particular devices and what they thought their functioning could tell us about the nature of embryological phenomena. (shrink)

Traditional accounts of explanation fail to illuminate the explanatory relevance of “models that are descriptively false” in the sense that the regularities they entail fail to obtain. In this paper, I propose an account of explanation, which I call ‘explanation by concretization’, that serves to explicate the explanatory relevance of such models. Starting from a highly abstract and idealized model, causal explanations of the absence of regularities are sought by adding complexity to the model or by concretizing it. Whether this (...) process is successful depends on whether the abstractions and idealizations in the basic model succeed in isolating a mechanism, i.e. in representing how it operates when interfering factors are absent. This account is developed in the context of economics and contrasted to those of Daniel Hausman and Nancy Cartwright. I go on to provide an account of how unrealistic models can be used for providing understanding of the way mechanisms work. (shrink)

Many of the arguments for neuroeconomics rely on mistaken assumptions about criteria of explanatory relevance across disciplinary boundaries and fail to distinguish between evidential and explanatory relevance. Building on recent philosophical work on mechanistic research programmes and the contrastive counterfactual theory of explanation, we argue that explaining an explanatory presupposition or providing a lower-level explanation does not necessarily constitute explanatory improvement. Neuroscientific findings have explanatory relevance only when they inform a causal and explanatory account of the psychology of human decision-making.

I distinguish three theses associated with the new mechanistic philosophy – concerning causation, explanation and scientific methodology. Advocates of each thesis are identified and relationships among them are outlined. I then look at some recent work on natural selection and mechanisms. There, attention to different kinds of New Mechanism significantly affects of what is at stake.

The concept of mechanism is analyzed in terms of entities and activities, organized such that they are productive of regular changes. Examples show how mechanisms work in neurobiology and molecular biology. Thinking in terms of mechanisms provides a new framework for addressing many traditional philosophical issues: causality, laws, explanation, reduction, and scientific change.

We provide an account of mechanistic representation and explanation that has several advantages over previous proposals. In our view, explaining mechanistically is not simply giving an explanation of a mechanism. Rather, an explanation is mechanistic because of particular relations that hold between a mechanical representation, or model, and the target of explanation. Under this interpretation, mechanistic explanation is possible even when the explanatory target is not a mechanism. We argue that taking this view is not only coherent and plausible, it (...) gives a more sophisticated view of the relationship between mechanical models and their targets. This allows us to address some ambiguities within the mechanist framework, and delivers a more intuitive way to interpret scientists' use of the term "mechanism". (shrink)

Jon Elster worries about the explanatory power of the social sciences. His main concern is that they have so few well-established laws. Elster develops an interesting substitute: a special kind of mechanism designed to fill the explanatory gap between laws and mere description. However, his mechanisms suffer from a characteristic problem that I will explore in this article. As our causal knowledge of a specific problem grows we might come to know too much to make use of an Elsterian mechanism (...) but still lack a law. We might then find ourselves in the paradoxical position of knowing more relevant causal truths about the phenomenon we are interested in than we did before, but being able to explain less. If this possibility is realized in social science settings, as I argue it might well be, Elster?s mechanistic account is threatened. Moreover, even if the possibility is rarely realized in that way, it raises, simply as a possibility, a conceptual problem with Elster?s mechanistic framework. (shrink)

Accounts of ontic explanation have often been devised so as to provide an understanding of mechanism and of causation. Ontic accounts differ quite radically in their ontologies, and one of the latest additions to this tradition proposed by Peter Machamer, Lindley Darden and Carl Craver reintroduces the concept of activity. In this paper I ask whether this influential and activity-based account of mechanisms is viable as an ontic account. I focus on polygenic scenarios—scenarios in which the causal truths depend on (...) more than one cause. The importance of polygenic causation was noticed early on by Mill (1893). It has since been shown to be a problem for both causal-law approaches to causation (Cartwright 1983) and accounts of causation cast in terms of capacities (Dupré 1993; Glennan 1997, pp. 605-626). However, whereas mechanistic accounts seem to be attractive precisely because they promise to handle complicated causal scenarios, polygenic causation needs to be examined more thoroughly in the emerging literature on activity-based mechanisms. The activity-based account proposed in Machamer et al. (2000, pp. 1-25) is problematic as an ontic account, I will argue. It seems necessary to ask, of any ontic account, how well it performs in causal situations where—at the explanandum level of mechanism—no activity occurs. In addition, it should be asked how well the activity-based account performs in situations where there are too few activities around to match the polygenic causal origin of the explanandum. The first situation presents an explanandum-problem and the second situation presents an explanans-problem—I will argue—both of which threaten activity-based frameworks. (shrink)

This paper is an attempt to further our understanding of mechanisms conceived of as ontologically separable from laws. What opportunities are there for a mechanistic perspective to be independent of, or even more fundamental than, a law perspective? Advocates of the mechanistic view often play with the possibility of internal and external reliability, or with the paralleling possibilities of enforcing, counteracting, redirecting, etc., the mechanisms’ power to produce To further this discussion I adopt a trope ontology. It is independent of (...) the notion of law, and can easily be adapted to account for such characteristics of mechanisms. The idea of tropes as mechanisms is worked out in some detail. According to the resulting picture, there is still an opportunity to link mechanisms and laws. But while the predominant law view conceives of mechanistic approaches as special kinds of law accounts, this study indicates that the converse may be true. Law accounts are special cases of mechanistic accounts, and they work only in those worlds where the mechanisms are of the right kind. (shrink)

This book highlights some of the conceptual problems that still need to be solved and points out a number of fresh philosophical ideas to explore.

We sketch a framework for building a unified science of cognition. This unification is achieved by showing how functional analyses of cognitive capacities can be integrated with the multilevel mechanistic explanations of neural systems. The core idea is that functional analyses are sketches of mechanisms , in which some structural aspects of a mechanistic explanation are omitted. Once the missing aspects are filled in, a functional analysis turns into a full-blown mechanistic explanation. By this process, functional analyses are seamlessly integrated (...) with multilevel mechanistic explanations. (shrink)

Natural kinds are often contrasted with other kinds of scientific kinds, especially functional kinds, because of a presumed categorical difference in explanatory value: supposedly, natural kinds can ground explanations, while other kinds of kinds cannot. I argue against this view of natural kinds by examining a particular type of explanation—mechanistic explanation—and showing that functional kinds do the same work there as traditionally recognized natural kinds are supposed to do in “standard” scientific explanations. Breaking down this categorical distinction between traditional natural (...) kinds and other kinds of kinds, I argue, delivers two goods: It provides us with a view of natural kindhood that does justice to the epistemic roles of kinds in scientific explanations. And it allows us to solve a problem that HPC theory, currently one of the more popular accounts of natural kindhood, confronts. † To contact the author, please write to: Center for Philosophy and Ethics of Science (ZEWW), Leibniz University of Hannover, Im Moore 21, 30167 Hannover, Germany; e‐mail: reydon@ww.uni‐hannover.de. (shrink)

General Process Theory (GPT) is a new (non-Whiteheadian) process ontology. According to GPT the domains of scientific inquiry and everyday practice consist of configurations of ‘goings-on’ or ‘dynamics’ that can be technically defined as concrete, dynamic, non-particular individuals called general processes. The paper offers a brief introduction to GPT in order to provide ontological foundations for research programs such as interactivism that centrally rely on the notions of ‘process,’ ‘interaction,’ and ‘emergence.’ I begin with an analysis of our common sense (...) concept of activities, which plays a crucial heuristic role in the development of the notion of a general process. General processes are not individuated in terms of their location but in terms of ‘what they do,’ i.e., in terms of their dynamic relationships in the basic sense of one process being part of another. The formal framework of GPT is thus an extensional mereology, albeit a non-classical theory with a non-transitive part-relation. After a brief sketch of basic notions and strategies of the GPT-framework I show how the latter may be applied to distinguish between causal, mechanistic, functional, self-maintaining, and recursively self-maintaining interactions, all of which involve ‘emergent phenomena’ in various senses of the term. (shrink)

In this paper we argue that dissociative identity disorder (DID) is best interpreted as a causal model of a (possible) post-traumatic psychological process, as a mechanical model of an abnormal psychological condition. From this perspective we examine and criticize the evidential status of DID, and we demonstrate that there is really no good reason to believe that anyone has ever suffered from DID so understood. This is so because the proponents of DID violate basic methodological principles of good causal modeling. (...) When every ounce of your concentration is fixed upon blasting a winged pig out of the sky, you do not question its species' ontological status. James Morrow, City of Truth (1990). (shrink)

In this paper, the relation between identity-based reduction and one specific sort of reductive explanation is considered. The notion of identity-based reduction is spelled out and its role in the reduction debate is sketched. An argument offered by Jaegwon Kim, which is supposed to show that identity-based reduction and reductive explanation are incompatible, is critically examined. From the discussion of this argument, some important consequences about the notion of reduction are pointed out.

Here I consider the relative merits of two recent models of explanation, James Woodward's interventionist-counterfactual model and the model model. According to the former, explanations are largely constituted by information about the consequences of counterfactual interventions. Problems arise for this approach because countless relevant interventions are possible in most cases and because it overlooks other kinds of equally relevant information. According the model model, explanations are largely constituted by cognitive models of actual mechanisms. On this approach, explanations tend not to (...) represent any of the aforementioned information explicitly but can instead be used to produce it on demand. The model model thus offers the more plausible account of the information of which we are aware when we have an explanation and of the ratiocinative process through which we derive many kinds of information that are relevant to the evaluation of explanations. (shrink)

Mechanistic explanation has an impressive track record of advancing our understanding of complex, hierarchically organized physical systems, particularly biological and neural systems. But not every complex system can be understood mechanistically. Psychological capacities are often understood by providing cognitive models of the systems that underlie them. I argue that these models, while superficially similar to mechanistic models, in fact have a substantially more complex relation to the real underlying system. They are typically constructed using a range of techniques for abstracting (...) the functional properties of the system, which may not coincide with its mechanistic organization. I describe these techniques and show that despite being non-mechanistic, these cognitive models can satisfy the normative constraints on good explanations. (shrink)

This paper is concerned with reasonings that purport to explain why certain organisms have certain traits by showing that their actual design is better than contrasting designs. Biologists call such reasonings ‘functional explanations’. To avoid confusion with other uses of that phrase, I call them ‘design explanations’. This paper discusses the structure of design explanations and how they contribute to scientific understanding. Design explanations are contrastive and often compare real organisms to hypothetical organisms that cannot possibly exist. They are not (...) causal but appeal to functional dependencies between an organism’s different traits. These explanations point out that because an organism has certain traits (e.g., it lives on land), it cannot be alive if the trait to be explained (e.g., having lungs) were replaced by a specified alternative (e.g., having gills). They can be understood from a mechanistic point of view as revealing the constraints on what mechanisms can be alive. (shrink)

The ontic conception of scientific explanation has been constructed and motivated on the basis of a putative lexical ambiguity in the term explanation. I raise a puzzle for this ambiguity claim, and then give a deflationary solution under which all ontically-rendered talk of explanation is merely elliptical; what it is elliptical for is a view of scientific explanation that altogether avoids the ontic conception. This result has revisionary consequences for New Mechanists and other philosophers of science, many of whom have (...) assimilated their conception of explanation to the ontic conception. (shrink)

As much as assumptions about mechanisms and mechanistic explanation have deeply affected psychology, they have received disproportionately little analysis in philosophy. After a historical survey of the influences of mechanistic approaches to explanation of psychological phenomena, we specify the nature of mechanisms and mechanistic explanation. Contrary to some treatments of mechanistic explanation, we maintain that explanation is an epistemic activity that involves representing and reasoning about mechanisms. We discuss the manner in which mechanistic approaches serve to bridge levels rather than (...) reduce them, as well as the different ways in which mechanisms are discovered. Finally, we offer a more detailed example of an important psychological phenomenon for which mechanistic explanation has provided the main source of scientific understanding. (shrink)

This paper is an attempt to further our understanding of mechanisms conceived of as ontologically separable from laws. What opportunities are there for a mechanistic perspective to be independent of, or even more fundamental than, a law perspective? Advocates of the mechanistic view often play with the possibility of internal and external reliability, or with the paralleling possibilities of enforcing, counteracting, redirecting, etc., the mechanisms’ power to produce To further this discussion I adopt a trope ontology. It is independent of (...) the notion of law, and can easily be adapted to account for such characteristics of mechanisms. The idea of tropes as mechanisms is worked out in some detail. According to the resulting picture, there is still an opportunity to link mechanisms and laws. But while the predominant law view conceives of mechanistic approaches as special kinds of law accounts, this study indicates that the converse may be true. Law accounts are special cases of mechanistic accounts, and they work only in those worlds where the mechanisms are of the right kind. (shrink)

Comparisons of rival explanations or theories often involve vague appeals to explanatory power. In this paper, we dissect this metaphor by distinguishing between different dimensions of the goodness of an explanation: non-sensitivity, cognitive salience, precision, factual accuracy and degree of integration. These dimensions are partially independent and often come into conflict. Our main contribution is to go beyond simple stipulation or description by explicating why these factors are taken to be explanatory virtues. We accomplish this by using the contrastive-counterfactual approach (...) to explanation and the view of understanding as an inferential ability. By combining these perspectives, we show how the explanatory power of an explanation in a given dimension can be assessed by showing the range of answers it provides to what-if-things-had-been-different questions and the theoretical and pragmatic importance of these questions. Our account also explains intuitions linking explanation to unification or to exhibition of a mechanism. (shrink)

This paper is about the problem of explanation in anthropology. There are, broadly speaking, three theories of explanation, namely, the scientific theory, the historical theory, and finally what I have decided to call the phenomenological theory, after M. Natanson. The author argues that none of the three theories is adequate by itself to encompass the complex nature of anthropological science. The three theories correspond roughly to at least three different types of questions raised by anthropologists, and this being the case (...) the principle of methodological tolerance seems a natural and sensible principle to adopt. The paper also deals with the problem of reduction, i.e. the problem whether the three theories are different from and logically independent of one another. (shrink)

It's been 41 years since the publication of Ernst Mayr's Cause and Effect in Biology wherein Mayr most clearly develops his version of the influential distinction between ultimate and proximate causes in biology. In critically assessing Mayr's essay I uncover false statements and red-herrings about biological explanation. Nevertheless, I argue to uphold an analogue of the ultimate/proximate distinction as it refers to two different kinds of explanations, one dynamical the other statistical.

In an incendiary 2010 Nature article, M. A. Nowak, C. E. Tarnita and E. O. Wilson present a savage critique of the best known and most widely used framework for the study of social evolution, W. D. Hamilton’s theory of kin selection. Over a hundred biologists have since rallied to the theory’s defence, but Nowak et al. maintain that their arguments ‘stand unrefuted’. Here I consider the most contentious claim Nowak et al. defend: that Hamilton’s rule, the core explanatory principle (...) of kin selection theory, ‘almost never holds’. I first distinguish two versions of Hamilton’s rule in contemporary theory: a special version (HRS) that requires restrictive assumptions, and a general version (HRG) that does not. I then show that Nowak et al. are most charitably construed as arguing that HRS almost never holds, while HRG buys its generality at the expense of explanatory power. While their arguments against HRS are fairly uncontroversial, their arguments against HRG are more contentious, yet these have been largely overlooked in the ensuing furore. I consider the arguments for and against the explanatory value of HRG, with a view to assessing what exactly is at stake in the debate. I suggest that the debate hinges on issues concerning the causal interpretability of regression coefficients, and concerning the explanatory function Hamilton’s rule is intended to serve. (shrink)

Any theory of explanation must account for the explanatory successes of statistical scientific theories. This should not be done by endorsing determinism. These considerations have been taken as sufficient ground for rejecting the demand on explanations to be deductive. The arguments for doing so, in Coffa (1974) and Salmon (1977, 1984, 1988), are, however, not persuasive. Deductivism is a viable position. Considering that doubts can be raised against the explanatory validity of probabilistic causal relations and the intuitive plausibility of deductivism, (...) it is also a recommendable position, though elaboration is needed in accounting for some of the uses of statistical theories in explanations. (shrink)

An argument has been recently proposed by Watkins, whose objective is to show the impossibility of a statistical explanation of single events. This present paper is an attempt to show that Watkins's argument is unsuccessful, and goes on to argue for an account of statistical explanation which has much in common with Hempel's classic treatment.

Causal modeling methods such as path analysis, used in the social and natural sciences, are also highly relevant to philosophical problems of probabilistic causation and statistical explanation. We show how these methods can be effectively used (1) to improve and extend Salmon's S-R basis for statistical explanation, and (2) to repair Cartwright's resolution of Simpson's paradox, clarifying the relationship between statistical and causal claims.

Numerous philosophers, among them Carl G. Hempel and Wesley C. Salmon, have attempted to explicate the notion of explanatory relevance in terms of the statistical relevance of various properties of an individual to the explanandum property itself (or what is here called narrow statistical relevance). This approach seems plausible if one assumes that to explain an occurrence is to show that it was to be expected or to exhibit its degree of expectability and the factors which influence its expectability. But (...) considerations of narrow statistical relevance do not provide an adequate basis for explanatory classification, and the aforementioned views of explanation are accordingly mistaken. Explanatory classification must provide at least a partial account of the nature of a thing, and such an account will generally go beyond what is required as a basis for correct expectation. (shrink)

Wesley Salmon has advanced a new model of explanations of particular facts which requires that the explanans contain laws. The laws used in explanations (according to this model) are of the form P(A· C1,B)=p1... P(A· Cn,B)=pn. A condition imposed by Salmon on these laws is that the reference classes, i.e. A· C1... A· Cn, be homogenous with reference to the property B. A reference class A is homogenous with reference to a property B if every property which determines a place (...) selection with reference to B within A is statistically irrelevant to B in A. It is argued here that the concept of homogeneity cannot in general be satisfied in scientific explanations and that even a weaker requirement, "epistemic homogeneity," may be too strong. (shrink)

The statistical interpretation of the Theory of Natural Selection claims that natural selection and drift are statistical features of mathematical aggregates of individual-level events. Natural selection and drift are not themselves causes. The statistical interpretation is motivated by a metaphysical conception of individual priority. Recently, Millstein, Skipper, and Dietrich (2009) have argued (a) that natural selection and drift are physical processes, and (b) that the statistical interpretation rests on a misconception of the role of mathematics in biology. Both theses are (...) contested. (shrink)

A hitherto neglected form of explanation is explored, especially its role in population genetics. “Statistically abstractive explanation” (SA explanation) mandates the suppression of factors probabilistically relevant to an explanandum when these factors are extraneous to the theoretical project being pursued. When these factors are suppressed, the explanandum is rendered uncertain. But this uncertainty traces to the theoretically constrained character of SA explanation, not to any real indeterminacy. Random genetic drift is an artifact of such uncertainty, and it is therefore wrong (...) to reify it as a cause of evolution or as a process in its own right. *Received July 2009. †To contact the author, please write to: Department of Philosophy, University of Toronto, 170 St. George St., Toronto, ON M5R 2M8, Canada; e‐mail: mohan.matthen@utoronto.ca. (shrink)

In this paper an attempt is made at developing the notion of a real and complete empirical explanation as excluding all forms of potential or incomplete explanations. This explanation is, however, no longer conceived as the proper aim of empirical science, for it can certainly be gleaned from recent epistemological publications that no comprehensive notion of a real and complete scientific explanation is likely to be constructed from within empirical science. Contrary to common understanding the empirical explanation, deductive-nomological as well (...) as statistical explanation, is considered here only as motive of scientific activities, i.e., as common aim of a transcending cooperation of scientific and non-scientific social practice. Following from this the proper aim of empirical science now consists in the development of practically relevant explanatory theories.This redetermination of the aim of scientific activities of empirical science also means criticism of the unification of deductive-nomological and statistical explanations, as it has been proposed by Wolfgang Stegmüller in his pragmatisch-epistemische Wende. For both forms of empirical explanation must be referred to fundamentally different kinds of practical relevance, the former playing a more important role in the advancement of social practice. Stegmüller's development of a comprehensive probabilistic notion of empirical explanation, as tied up to pragmatic knowledge-situations, in a way already transcends a scientifically immanent determination of it, but he seems to have stopped halfway on the road to practically relevant empirical explanations. Several insufficiencies with his probabilistic notion of empirical explanation are shown up in this paper as a consequence of his abiding by pragmatic, and not penetrating to practical, knowledge-situations. The final result of it, however, consists in a clarification and a modification of the concept of deductive-nomological explanation, originally developed by Hempel and Oppenheim. (shrink)

Since the publication of Carl Hempel and Paul Oppenheim's ground-breaking work "Studies in the Logic of Explanation," the theory of explanation has remained a major topic in the philosophy of science. This valuable collection provides readers with the opportunity to study some of the classic essays on the theory of explanation along with the best examples of the most recent work being done on the topic. In addition to the original Hempel and Oppenheim paper, the volume includes Scriven's critical reaction (...) to it, Wilfrid Sellars's discussion of the problem of theoretical explanation, and pieces by Salmon, Railton, van Fraassen, Friedman, Kitcher, and Achinstein in which they demonstrate the vitality of the subject by extending the scope of the inquiry. (shrink)

It has been the dominant view that probabilistic explanations of particular facts must be inductive in character. I argue here that this view is mistaken, and that the aim of probabilistic explanation is not to demonstrate that the explanandum fact was nomically expectable, but to give an account of the chance mechanism(s) responsible for it. To this end, a deductive-nomological model of probabilistic explanation is developed and defended. Such a model has application only when the probabilities occurring in covering laws (...) can be interpreted as measures of objective chance, expressing the strength of physical propensities. Unlike inductive models of probabilistic explanation, this deductive model stands in no need of troublesome requirements of maximal specificity or epistemic relativization. (shrink)

In an explanation, what does the explaining and what gets explained? What are the relata of the explanation relation? Candidates include: people, events, facts, sentences, statements, and propositions.

Carl G. Hempel has often stated that inductive-statistical explanations, as he conceives them, are inductive arguments. This discussion note raises the question of whether such arguments are to be understood as (1) arguments of the traditional sort, containing premises and conclusions, governed by some sort of inductive "acceptance rules," or (2) something more closely akin to Carnap's degree of confirmation statements which occur in an inductive logic which entirely eschews inductive "acceptance rules." Hempel's writings do not seem unequivocal on this (...) issue. It is suggested that adoption of construal (2) would remove the need for Hempel's high probability requirement on I-S explanations. (shrink)

Through his S–R model of statistical relevance, Wesley Salmon offers a solution to the scientific explanation of objectively improbable events.

A consideration of some basic problems that arise in the attempt to provide an adequate characterization of statistical explanation is taken to show that an understanding of the nature of scientific explanation requires us to deal with the philosophical problems connected with the nature of prior probabilities.

The statistical aspects of quantum explanation are intrinsic to quantum physics; individual quantum events are created in the interactions associated with observation and are not describable by predictive theory. The superposition principle shows the essential difference between quantum and non-quantum physics, and the principle is exemplified in the classic single-photon two-slit interference experiment. Recently Mandel and Pfleegor have done an experiment somewhat similar to the optical single-photon experiment but with two independently operated lasers; interference is obtained even with beam intensity (...) so small that only one photon is in the apparatus at a time. The result can be understood in terms of the superposition of states; or, in terms of the Uncertainty Principle, which is found to forbid the determination of which of the two lasers is the source of a given photon (if conditions for interference are to obtain). The Mandel-Pfleegor experiment gives a physical argument against the continuous localization of a photon that is assumed in the hidden variable theories and therefore gives further support for the generally accepted view that an observed entity (observed state) is created in the observation event. This aspect of quantum physics implies a subjectivism on the level of individual quantum-level occurrences, since there is in quantum theory no basis for asserting the existence of the event independently of observation of it. Extension of this subjectivism to large scale, non-quantum phenomena falls within the principles of quantum theory; counter considerations that argue against such an extension are noted. (shrink)

Some philosphers of science of an empiricist and pragmatist bent have proposed models of statistical explanation, but have then become sceptical of the adequacy of these models. It is argued that general considerations concerning the purpose of function of explanation in science which are usually appealed to by such philosophers show that their scepticism is not well taken; for such considerations provide much the same rationale for the search for statistical explanations, as these philosophers have characterized them, as they do (...) for lawlike explanations. But, it is further argued, a significant piece of what is frequently offered as an explanation of well known phenomena in statistical mechanics, fails to meet this general "pragmatic rationale" for statistical, or indeed any kind of, explanation. The question then arises whether the physicists have misconstrued the value of this piece of physical theorizing, ergodic theory, taking it to be explanatory when it is actually not; or whether, instead, the philosopher's account of just what is genuinely explanatory is too narrow. (shrink)

Approaches to explanation -- Causal and explanatory relevance -- The kairetic account of /D making -- The kairetic account of explanation -- Extending the kairetic account -- Event explanation and causal claims -- Regularity explanation -- Abstraction in regularity explanation -- Approaches to probabilistic explanation -- Kairetic explanation of frequencies -- Kairetic explanation of single outcomes -- Looking outward -- Looking inward.

It is widely held that the size of a probability makes no difference to the quality of a probabilistic explanation. I argue that explanatory practice in statistical physics belies this claim. The claim has gained currency only because of an impoverished conception of probabilistic processes and an unwarranted assumption that all probabilistic explanations have a single form.

The roles of linguistic, cognitive, and social-pragmatic processes in word learning are well established. If statistical mechanisms also contribute to word learning, they must interact with these processes; however, there exists little evidence for such mechanistic synergy. Adults use co-occurrence statistics to encode speech–object pairings with detailed sensitivity in stochastic learning environments (Vouloumanos, 2008). Here, we replicate this statistical work with nonspeech sounds and compare the results with the previous speech studies to examine whether exclusion constraints contribute equally to the (...) statistical learning of speech–object and nonspeech–object associations. In environments in which performance could benefit from exclusion, we find a learning advantage for speech over nonspeech, revealing an interaction between statistical and exclusion processes in associative word learning. (shrink)

The aim of this paper is to analyse the role that the distinction between principle and constructive theories have in the question of the explanatory power of Special Relativity. We show how the distinction breaks down at the explanatory level. We assess Harvey Brown’s (2005) claim that, as a principle theory, Special Relativity lacks of explanatory power and criticize it, as, we argue, based upon an unrealistic picture of the kind of explanations provided by principle (and constructive) theories. Finally, we (...) claim that the structural account of explanation (Hughes 1989b) captures the explanatory success of Special Relativity. (shrink)

Causalists about explanation claim that to explain an event is to provide information about the causal history of that event. Some causalists also endorse a proportionality claim, namely that one explanation is better than another insofar as it provides a greater amount of causal information. In this chapter I consider various challenges to these causalist claims. There is a common and influential formulation of the causalist requirement – the ‘Causal Process Requirement’ – that does appear vulnerable to these anti-causalist challenges, (...) but I argue that they do not give us reason to reject causalism entirely. Instead, these challenges lead us to articulate the causalist requirement in an alternative way. This alternative articulation incorporates some of the important anti-causalist insights without abandoning the explanatory necessity of causal information. For example, proponents of the ‘equilibrium challenge’ argue that the best available explanations of the behaviour of certain dynamical systems do not appear to provide any causal information. I respond that, contrary to appearances, these equilibrium explanations are fundamentally causal, and I provide a formulation of the causalist thesis that is immune to the equilibrium challenge. I then show how this formulation is also immune to the ‘epistemic challenge’ – thus vindicating (a properly formulated version of) the causalist thesis. (shrink)

In this paper I argue that the common practice of employing moral predicates as explaining phrases can be accommodated on an expressivist account of moral practice. This account does not treat moral explanations as in any way second-rate or derivative, since it subsumes moral explanations under the general theory of program explanations (as defended by Jackson and Pettit). It follows that the phenomenon of moral explanations cannot be used to adjudicate the debate between expressivism and its rivals.